def detect_local_minimum_two(fc, structure):
"""
Take a local minimum and detect nearby local minimum via extended gradient walks.
If a lower energy structure within radius 2 is detected (lower than the local minimum
of a normal gradient walk), then another gradient walk is applied for the lower structure.
"""
deepest_neighbor = None
deepest_neighbor_ddG = 1
pt = RNA.IntVector(RNA.ptable(structure))
neigh = fc.neighbors(pt, RNA.MOVESET_DELETION | RNA.MOVESET_INSERTION)
for nb in neigh:
dG_nb = fc.eval_move_pt(pt, nb.pos_5, nb.pos_3)
pt_nb = RNA.IntVector(move_apply(pt, nb))
neigh_2 = fc.neighbors(pt_nb,
RNA.MOVESET_DELETION | RNA.MOVESET_INSERTION)
for nb_2 in neigh_2:
dG_nb2 = fc.eval_move_pt(pt_nb, nb_2.pos_5, nb_2.pos_3)
ddG = dG_nb + dG_nb2
if ddG < 0 and ddG < deepest_neighbor_ddG:
deepest_neighbor_ddG = ddG
deepest_neighbor = move_apply(pt_nb, nb_2)
if deepest_neighbor:
deepest_neighbor = detect_local_minimum(
fc, RNA.db_from_ptable(deepest_neighbor))
return detect_local_minimum_two(fc, deepest_neighbor)
else:
return structure
def detect_local_minimum(fc, structure):
# perform gradient walk from sample to determine direct local minimum
pt = RNA.IntVector(RNA.ptable(structure))
fc.path(pt, 0, RNA.PATH_DEFAULT | RNA.PATH_NO_TRANSITION_OUTPUT)
return RNA.db_from_ptable(list(pt))
# read a list of sample structures and produce list of local minima for it
if nonredundant_sample_file:
lmin_nonred_file = "local_minima_nonred.txt"
nonredundant_samples = []
with open(nonredundant_sample_file) as f:
nonredundant_samples = f.readlines()
nonredundant_samples = [x.strip() for x in nonredundant_samples]
nonredundant_samples.pop(0)
nonredundant_minima = dict()
for s in nonredundant_samples:
pt = RNA.IntVector(RNA.ptable(s))
fc_base.path(pt, 0, RNA.PATH_DEFAULT | RNA.PATH_NO_TRANSITION_OUTPUT)
ss = RNA.db_from_ptable(list(pt))
if ss not in nonredundant_minima:
nonredundant_minima[ss] = {
'count': 1,
'energy': fc_base.eval_structure(ss)
}
new_minima = new_minima + 1
else:
nonredundant_minima[ss][
'count'] = nonredundant_minima[ss]['count'] + 1
f = open(lmin_nonred_file, 'w')
f.write(" %s\n" % sequence)
for i, s in enumerate(
